Content, such as a video, a live stream, an eSports event, etc., may be distributed to multiple users concurrently. For example, thousands of users may watch a live eSports event pertaining to a soccer game. Users may desire to share their emotional feelings and reactions while viewing the content. In an example, user chat interfaces of a chat room may be provided to the users while viewing the content. In this way, the users may share messages with one another through the chat room. However, the chat room may grow to a significant number of users as more users view the content (e.g., thousands of users may be using the chat room to discuss the live eSports event). Unfortunately, the chat room may become overwhelming to the point that users are unable to have meaningful interactions. Users may be unable to single out and/or participate in a certain conversation because text of the chat room may scroll too fast. Thus, users may become overwhelmed, and the chat room may become useless such as for sharing emotional reactions. Also, the chat room interface may experience performance issues such as lag due to resource strain, such as bandwidth consumption and client device resource consumption, from attempting to keep the chat room interface up-to-date with all the messages being generated by the thousands of users.
In another example, live video streams of users may be captured and displayed to other users for sharing user emotions and reactions to viewing the content. However, a live video stream may consume a significant amount of computing resources and network bandwidth to capture, transmit to other users, and display. Thus, live video streams may be limited to merely a few users. Chat rooms, live video streams, and other sharing techniques of user emotions may be very disruptive to the user experience (e.g., the user may stop watching content in order to type out or select an emotion to share) and resource intensive.